Environmental Bioinformatics and Computational Toxicology Center
EPA Grant Number: R832721Center: New Jersey Research Center for Environmental Bioinformatics and Computational Toxicology
Center Director: Welsh, William J.
Title: Environmental Bioinformatics and Computational Toxicology Center
Investigators: Welsh, William J. , Georgopoulos, Panos G.
Institution: University of Medicine and Dentistry of New Jersey , Princeton University , Rutgers, The State University of New Jersey
EPA Project Officer: Pascual, Pasky
Project Period: October 1, 2005 through September 30, 2010
Project Amount: $5,422,135
RFA: Computational Toxicology: Environmental Bioinformatics Research Center (2004) RFA Text | Recipients Lists
Research Category: Health , Safer Chemicals , Health Effects , Computational Toxicology
Objective:
The Research Center will bring together a team of computational scientists, with diverse backgrounds in bioinformatics, cheminformatics and enviroinformatics, from UMDNJ, Rutgers, and Princeton Universities, and the USFDA’s Center for Toxicoinformatics. This team will address, in a systematic and integrative manner, multiple elements of the toxicant Source-to-Outcome sequence ( Investigational Area 1, as identified in the RFA) as well as develop cheminformatics tools for toxicant characterization ( Investigational Area 2, Predictive Models for Hazard Identification ). The computational tools to be developed through this effort will be extensively evaluated and refined through collaborative applications involving Center scientists as well as colleagues from the three universities and USEPA; particular emphasis will be on methods that enhance current quantitative risk assessment practices and reduce uncertainties.
Approach:
The proposed Center will address a wide range of issues in Investigational Areas 1 and 2 and, furthermore, will pursue complementary applications in risk assessment ( Investigational Area 3 ). This will be achieved with the requested resources, by building upon a variety of methods and software systems recently developed at UMDNJ, Rutgers, Princeton (with funding from USEPA, USDOE, NIH and NSF), and USFDA. Research activities over the proposed 5-year effort will be organized in five projects; each project will develop a set of “stand-alone" components addressing specific problems of computational toxicology. Furthermore, Research Project 1 will provide an integrative framework for Investigational Area 1 while Project 4 will address the core issues of Area 2. Extensive interaction as well as public outreach and training activities will constitute essential elements of the Center and will be tightly interwoven with the research activities.
Expected Results:
Research Project 1 (Development and Application of a Dose-Response Information Analysis [DORIAN] System) will provide an integrative framework for the outcomes of the other projects. This framework will include the following components: a web-accessible Environmental Bioinformatics Knowledge Base (EBKB) that will provide a user-oriented interface to an extensive set of information and modeling resources; the ebTrack integrated analysis system that will include linkages to multiple (public and commercial) computational and database systems; Bayesian computational tools for characterizing and reducing uncertainties in mechanistic modeling of toxicity pathways; diagnostic computational tools for sensitivity and stability analysis of mechanistic models and statistical methods for data analysis; and enhanced tools for quantitative risk assessment (QRA) applications (e.g. for cross-species extrapolation, chemical mixtures, and dose-response).
Research Project 2 (Hepatocyte Metabolism Model for Xenobiotics) will develop tools for identifying maximally informative sets of toxicologically relevant genes; tools for analysis of toxicologically relevant regulatory networks; an expanded version of the Rutgers hepatocyte metabolism model that will incorporate transformations of xenobiotics; and tools for the analysis of transcriptional regulation that will allow assessing changes in hepatocyte phenotypic phase space.
Research Project 3 (Tools for Optimal Identification of Biological Networks) will develop efficient identification tools for inferring biological network structure from available laboratory data; optimization tools for extracting quantitative information of biological system parameters (rate constants, diffusion coefficients, binding affinities, etc.); global sensitivity analysis tools for identifying most effective molecular targets or pathways of biological networks and for guiding the design of laboratory experiments; and optimal feedback control tools for inferring networks with feedback loops.
Research Project 4 (Cheminformatics Tools for Toxicant Characterization) will develop an integrative hierarchical decision-forest framework for toxicant characterization that encompasses several novel technologies, including the Shape Signatures tool that rapidly matches organic and organometallic chemicals with each other or, alternatively, against target receptor sites/subsites; the Polynomial Neural Network (PNN) that automatically generates physically-intuitive linear or non-linear QSAR models; and virtual high-throughput screening (vHTS) methods that predict ligand binding affinity and provide mechanistic information (toxicity pathways).
Research Project 5 (Optimization Tools for In Silico Proteomics) will customize computational methods for protein structure prediction and de novo protein design, with specific focus on the important families of Glutathione Transferases (GST) (cytosolic, mitochondrial and microsomal GST); develop and implement computational methods for elucidating the topology of signal transduction networks and addressing uncertainties in experimental data and models; and develop de novo computational proteomics methods for peptide and protein identification via tandem mass spectroscopy.
Journal Articles: 103 Displayed | Download in RIS Format
| Other center views: | All 301 publications | 117 publications in selected types | All 103 journal articles |
|---|
| Type | Citation | ||
|---|---|---|---|
|
|
Ai N, Krasowski MD, Welsh WJ, Ekins S. Understanding nuclear receptors using computational methods. Drug Discovery Today 2009;14(9-10):486-494. |
R832721 (2008) |
Exit |
|
|
Almon RR, Yang E, Lai W, Androulakis IP, Ghimbovschi S, Hoffman EP, Jusko WJ, DuBois DC. Relationships between circadian rhythms and modulation of gene expression by glucocorticoids in skeletal muscle. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 2008;295(4):R1031-R1047. |
R832721 (2008) |
Exit Exit Exit |
|
|
Almon RR, Yang E, Lai W, Androulakis IP, DuBois DC, Jusko WJ. Circadian variations in rat liver gene expression: relationships to drug actions. Journal of Pharmacology and Experimental Therapeutics 2008;326(3):700-716. |
R832721 (2008) |
Exit Exit Exit |
|
|
Androulakis IP, Yang E, Almon RR. Analysis of time-series gene expression data:methods, challenges, and opportunities. Annual Review of Biomedical Engineering 2007;9:205-228. |
R832721 (2007) |
Exit |
|
|
Baliban RC, DiMaggio PA, Plazas-Mayorca MD, Young NL, Garcia BA, Floudas CA. A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry. Molecular and Cellular Proteomics 2010;9(5):764-779. |
R832721 (Final) |
Exit Exit Exit |
|
|
Bellows ML, Fung HK, Taylor MS, Floudas CA, Lopez de Victoria A, Morikis D. New compstatin variants through two de novo protein design frameworks. Biophysical Journal 2010;98(10):2337-2346. |
R832721 (Final) |
Exit |
|
|
Brell G, Li G, Rabitz H. An efficient algorithm to accelerate the discovery of complex material formulations. The Journal of Chemical Physics 2010;132(17):174103-174110. |
R832721 (Final) |
Exit |
|
|
Chekmarev DS, Kholodovych V, Balakin KV, Ivanenkov Y, Ekins S, Welsh WJ. Shape signatures: new descriptors for predicting cardiotoxicity in silico. Chemical Research in Toxicology 2008;21(6):1304-1314. |
R832721 (2008) |
Exit |
|
|
Chekmarev D, Kholodovych V, Kortagere S, Welsh WJ, Ekins S. Predicting inhibitors of acetylcholinesterase by regression and classification machine learning approaches with combinations of molecular descriptors. Pharmaceutical Research 2009;26(9):2216-2224. |
R832721 (2008) |
Exit |
|
|
Chen M, Martin J, Fang H, Isukapalli S, Georgopoulos PG, Welsh WJ, Tong W. ebTrack: an environmental bioinformatics system built upon ArrayTrackTM. BMC Proceedings 2009;3(Suppl 2):S5. |
R832721 (2008) |
Exit Exit Exit |
|
|
Cohen Hubal EA, Richard A, Aylward L, Edwards S, Gallagher J, Goldsmith M-R, Isukapalli S, Tornero-Velez R, Weber E, Kavlock R. Advancing exposure characterization for chemical evaluation and risk assessment. Journal of Toxicology and Environmental Health-Part B-Critical Reviews 2010;13(2-4):299-313. |
R832721 (Final) |
Exit |
|
|
Davis E, Ierapetritou M. A kriging method for the solution of nonlinear programs with black-box functions. AIChE Journal 2007;53(8):2001-2012. |
R832721 (2007) |
Exit Exit |
|
|
Davis E, Ierapetritou M. A centroid-based sampling strategy for kriging global modeling and optimization. AIChE Journal 2010;56(1):220-240. |
R832721 (2008) |
Exit |
|
|
DiMaggio Jr PA, Floudas CA. De novo peptide identification via tandem mass spectrometry and integer linear optimization. Analytical Chemistry 2007;79(4):1433-1446. |
R832721 (2007) |
|
|
|
DiMaggio Jr PA, Floudas CA. A mixed-integer optimization framework for de novo peptide identification. AIChE Journal 2007;53(1):160-173. |
R832721 (2007) R832721C005 (2006) |
|
|
|
DiMaggio Jr. PA, Floudas CA, Lu B, Yates III JR. A hybrid method for peptide identification using integer linear optimization, local database search, and quadrupole time-of-flight or OrbiTrap tandem mass spectrometry. Journal of Proteome Research 2008;7(4):1584-1593. |
R832721 (2008) |
Exit |
|
|
DiMaggio Jr PA, McAllister SR, Floudas CA, Feng X-J, Rabinowitz JD, Rabitz HA. Optimal methods for re-ordering data matrices in systems biology and drug discovery applications. Biophysical Reviews and Letters 2008;3(1-2):19-42. |
R832721 (2008) |
Exit |
|
|
DiMaggio Jr PA, McAllister SR, Floudas CA, Feng X-J, Rabinowitz JD, Rabitz HA. Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies. BMC Bioinformatics 2008;9:458-473. |
R832721 (2008) |
Exit Exit Exit |
|
|
DiMaggio Jr. PA, McAllister SR, Floudas CA, Feng X-J, Rabinowitz JD, Rabitz HA. Enhancing molecular discovery using descriptor-free rearrangement clustering techniques for sparse data sets. AIChE Journal 2010;56(2):405-418. |
R832721 (Final) |
Exit |
|
|
DiMaggio Jr PA, McAllister SR, Floudas CA, Feng X-J, Rabinowitz JD, Rabitz HA. A network flow model for biclustering via optimal re-ordering of data matrices. Journal of Global Optimization 2010;47(3):343-354. |
R832721 (2008) R832721 (Final) |
Exit Exit |
|
|
DiMaggio Jr. PA, Subramani A, Judson RS, Floudas CA. A novel framework for predicting in vivo toxicities from in vitro data using optimal methods for dense and sparse matrix re-ordering and logistic regression. Toxicological Sciences 2010;118(1):251-265. |
R832721 (Final) |
Exit Exit Exit |
|
|
DiMaggio Jr. PA, Young NL, Baliban RC, Garcia BA, Floudas CA. A mixed integer linear optimization framework for the identification and quantification of targeted post-translational modifications of highly modified proteins using multiplexed electron transfer dissociation tandem mass spectrometry. Molecular and Cellular Proteomics 2009;8(11):2527-2543. |
R832721 (Final) |
Exit Exit Exit |
|
|
Dong X, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes. PLoS One 2010;5(2):e9249. |
R832721 (Final) |
Exit Exit Exit |
|
|
Efstathiou C, Isukapalli S, Georgopoulos P. A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens. Atmospheric Environment 2011;45(13):2260-2276. |
R832721 (Final) R834547 (2010) |
Exit Exit Exit |
|
|
Ekins S, Chang C, Mani S, Krasowski MD, Reschly EJ, Iyer M, Kholodovych V, Ai N, Welsh WJ, Sinz M, Swaan PW, Patel R, Bachmann K. Human pregnane X receptor antagonists and agonists define molecular requirements for different binding sites. Molecular Pharmacology 2007;72(3):592-603. |
R832721 (2007) |
|
|
|
Ekins S, Kholodovych V, Ai N, Sinz M, Gal J, Gera L, Welsh WJ, Bachmann K, Mani S. Computational discovery of novel low micromolar human pregnane X receptor antagonists. Molecular Pharmacology 2008;74(3):662-672. |
R832721 (2008) |
Exit Exit Exit |
|
|
Feng X, Sanchis J, Reetz MT, Rabitz H. Enhancing the efficiency of directed evolution in focused enzyme libraries by the adaptive substituent reordering algorithm. Chemistry-A European Journal 2012;18(18):5646-5654. |
R832721 (Final) |
Exit |
|
|
Floudas CA. Computational methods in protein structure prediction. Biotechnology and Bioengineering 2007;97(2):207-213. |
R832721 (2007) |
Exit Exit |
|
|
Foteinou PT, Yang E, Androulakis IP. Networks, biology and systems engineering: a case study in inflammation. Computers & Chemical Engineering 2009;33(12):2028-2041. |
R832721 (Final) |
Exit Exit |
|
|
Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Translational potential of systems-based models of inflammation. Clinical and Translational Science 2009;2(1):85-89. |
R832721 (2008) |
Exit |
|
|
Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Modeling endotoxin-induced systemic inflammation using an indirect response approach. Mathematical Biosciences 2009;217(1):27-42. |
R832721 (2008) |
Exit |
|
|
Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. In silico simulation of corticosteroids effect on an NFkB-dependent physicochemical model of systemic inflammation. PLoS One 2009;4(3):e4706. |
R832721 (2008) |
Exit Exit Exit |
|
|
Foteinou PT, Yang E, Saharidis GK, Ierapetritou MG, Androulakis IP. A mixed-integer optimization framework for the synthesis and analysis of regulatory networks. Journal of Global Optimization 2009;43(2-3):263-276. |
R832721 (2008) |
Exit |
|
|
Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Multiscale model for the assessment of autonomic dysfunction in human endotoxemia. Physiological Genomics 2010;42(1):5-19. |
R832721 (Final) |
Exit Exit Exit |
|
|
Fung HK, Welsh WJ, Floudas CA. Computational de novo peptide and protein design: rigid templates versus flexible templates. Industrial & Engineering Chemistry Research 2008;47(4):993-1001. |
R832721 (2007) R832721 (2008) |
Exit Exit |
|
|
Fung HK, Floudas CA, Taylor MS, Zhang L, Morikis D. Toward full-sequence de novo protein design with flexible templates for human beta-defensin-2. Biophysical Journal 2008;94(2):584-599. |
R832721 (2008) |
Exit Exit Exit |
|
|
Georgopoulos PG. A multiscale approach for assessing the interactions of environmental and biological systems in a holistic health risk assessment framework. Water, Air, & Soil Pollution: Focus 2008;8(1):3-21. |
R832721 (2007) R832721 (2008) R832721 (Final) R832721C001 (2006) R832721C001 (2007) |
Exit Exit |
|
|
Georgopoulos PG, Sasso AF, Isukapalli SS, Lioy PJ, Vallero DA, Okino M, Reiter L. Response to "µg/kg-day or µg/day? A commentary on Georgopoulos et al., JESEE 2008." Journal of Exposure Science & Environmental Epidemiology 2008;18(6):536-537 (author reply). |
R832721 (2008) |
Exit Exit |
|
|
Georgopoulos PG, Wang S-W, Yang Y-C, Xue J, Zartarian VG, McCurdy T, Ozkaynak H. Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic. Journal of Exposure Science & Environmental Epidemiology 2008;18(5):462-476. |
R832721 (2008) |
Exit Exit Exit |
|
|
Georgopoulos PG, Sasso AF, Isukapalli SS, Lioy PJ, Vallero DA, Okino M, Reiter L. Reconstructing population exposures to environmental chemicals from biomarkers: challenges and opportunities. Journal of Exposure Science & Environmental Epidemiology 2009;19(2):149-171. |
R832721 (2008) |
Exit Exit Exit |
|
|
Gerecke DR, Chen M, Isukapalli SS, Gordon MK, Chang Y-C, Tong W, Androulakis IP, Georgopoulos PG. Differential gene expression profiling of mouse skin after sulfur mustard exposure: extended time response and inhibitor effect. Toxicology and Applied Pharmacology 2009;234(2):156-165. |
R832721 (2008) |
Exit Exit Exit |
|
|
Isukapalli SS, Lioy PJ, Georgopoulos PG. Mechanistic modeling of emergency events: assessing the impact of hypothetical releases of anthrax. Risk Analysis 2008;28(3):723-740. |
R832721 (2008) |
Exit |
|
|
Iyer VV, Ovacik MA, Androulakis IP, Roth CM, Ierapetritou MG. Transcriptional and metabolic flux profiling of triadimefon effects on cultured hepatocytes. Toxicology and Applied Pharmacology 2010;248(3):165-177. |
R832721 (Final) |
Exit Exit |
|
|
Iyer VV, Yang H, Ierapetritou MG, Roth CM. Effects of glucose and insulin on HepG2-C3A cell metabolism. Biotechnology and Bioengineering 2010;107(2):347-356. |
R832721 (2008) R832721 (Final) |
Exit |
|
|
Izmailov S, Feng XJ, Li G, Rabitz H. A scalable algorithm for molecular property estimation in high dimensional scaffold-based libraries. Journal of Mathematical Chemistry 2012;50(7):1765-1790. |
R832721 (Final) |
Exit |
|
|
Jiao Y, Su M, Chen M, Jia W, Chou Y, Huang Z, Yang N, Tong W. LC/ESI-MS method for the determination of trimetazidine in human plasma: application to a bioequivalence study on Chinese volunteers. Journal of Pharmaceutical and Biomedical Analysis 2007;43(5):1804-1807. |
R832721 (2007) |
Exit Exit |
|
|
Jornsten R, Ouyang M, Wang H-Y. A meta-data based method for DNA microarray imputation. BMC Bioinformatics 2007;8:109. |
R832721 (2007) |
|
|
|
Jornsten R, Keles S. Mixture models with multiple levels, with application to the analysis of multifactor gene expression data. Biostatistics 2008;9(3):540-554. |
R832721 (2008) |
Exit Exit Exit |
|
|
Jornsten R. Simultaneous model selection via rate-distortion theory, with applications to cluster and significance analysis of gene expression data. Journal of Computational & Graphical Statistics 2009;18(3):613-639. |
R832721 (2007) |
Exit |
|
|
Kortagere S, Chekmarev D, Welsh WJ, Ekins S. New predictive models for blood-brain barrier permeability of drug-like molecules. Pharmaceutical Research 2008;25(8):1836-1845. |
R832721 (2008) |
Exit |
|
|
Kortagere S, Ekins S, Welsh WJ. Halogenated ligands and their interactions with amino acids: implications for structure-activity and structure-toxicity relationships. Journal of Molecular Graphics and Modelling 2008;27(2):170-177. |
R832721 (2008) |
Exit |
|
|
Lerapetritou MG, Georgopoulos PG, Roth CM, Androulakis IP. Tissue-level modeling of xenobiotic metabolism in liver: an emerging tool for enabling clinical translational research. Clinical and Translational Science 2009;2(3):228-237. |
R832721 (2008) |
Exit |
|
|
Li C-W, Ai N, Dinh GK, Welsh WJ, Chen JD. Human ADA3 regulates RARα transcriptional activity through direct contact between LxxLL motifs and the receptor coactivator pocket. Nucleic Acids Research 2010;38(16):5291-5303. |
R832721 (2008) R832721 (Final) |
Exit Exit Exit |
|
|
Li G, Rabitz H, Hu J, Chen Z, Ju Y. Regularized random-sampling high dimensional model representation (RS-HDMR). Journal of Mathematical Chemistry 2008;43(3):1207-1232. |
R832721 (2007) R832721 (2008) |
Exit |
|
|
Li G, Rabitz H, Yelvington PE, Oluwole OO, Bacon F, Kolb CE, Schoendorf J. Global sensitivity analysis for systems with independent and/or correlated inputs. Journal of Physical Chemistry A 2010;114(19):6022-6032. |
R832721 (2008) R832721 (Final) |
Exit |
|
|
Li G, Rabitz H. D-MORPH regression: application to modeling with unknown parameters more than observation data. Journal of Mathematical Chemistry 2010;48(4):1010-1035. |
R832721 (Final) |
Exit |
|
|
McAllister SR, Mickus BE, Klepeis JL, Floudas CA. Novel approach for α-helical topology prediction in globular proteins:generation of interhelical restraints. Proteins:Structure, Function, and Bioinformatics 2006;65(4):930-952. |
R832721 (2007) |
|
|
|
McAllister SR, Floudas CA. α-helical topology prediction and generation of distance restraints in membrane proteins. Biophysical Journal 2008;95(11):5281-5295. |
R832721 (2008) |
Exit Exit Exit |
|
|
McAllister SR, Rajgaria R, Floudas CA. A path selection approach to global pairwise sequence alignment using integer linear optimization. Optimization: A Journal of Mathematical Programming and Operations Research 2008;57(1):101-111. |
R832721 (2008) |
Exit |
|
|
McAllister SR, Feng X-J, DiMaggio Jr PA, Floudas CA, Rabinowitz JD, Rabitz H. Descriptor-free molecular discovery in large libraries by adaptive substituent reordering. Bioorganic & Medicinal Chemistry Letters 2008;18(22):5967-5970. |
R832721 (2008) |
Exit Exit |
|
|
McAllister SR, Floudas CA. Enhanced bounding techniques to reduce the protein conformational search space. Optimization Methods & Software 2009;24(4-5):837-855. |
R832721 (2008) |
Exit |
|
|
McAllister SR, DiMaggio Jr PA, Floudas CA. Mathematical modeling and efficient optimization methods for the distance-dependent rearrangement clustering problem. Journal of Global Optimization 2009;45(1):111-129. |
R832721 (2008) |
Exit |
|
|
McAllister SR, Floudas CA. An improved hybrid global optimization method for protein tertiary structure prediction. Computational Optimization and Applications 2010;45(2):377-413. |
R832721 (2008) R832721 (Final) |
Exit |
|
|
Nguyen TT, Nowakowski RS, Androulakis IP. Unsupervised selection of highly coexpressed and noncoexpressed genes using a consensus clustering approach. OMICS 2009;13(3):219-237. |
R832721 (2008) |
Exit |
|
|
Nguyen TT, Almon RR, DuBois DC, Jusko WJ, Androulakis IP. Importance of replication in analyzing time-series gene expression data: corticosteroid dynamics and circadian patterns in rat liver. BMC Bioinformatics 2010;11:279. |
R832721 (Final) |
Exit Exit Exit |
|
|
Nguyen TT, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP. Computational identification of transcriptional regulators in human endotoxemia. PLoS One 2011;6(5):e18889. |
R832721 (Final) |
Exit Exit Exit |
|
|
Oelschlaeger P, Ai N, DuPrez KT, Welsh WJ, Toney JH. Evolving carbapenemases: can medicinal chemists advance one step ahead of the coming storm? Journal of Medicinal Chemistry 2010;53(8):3013-3027. |
R832721 (Final) |
Exit |
|
|
Ovacik MA, Androulakis IP. On the potential for integrating gene expression and metabolic flux data. Current Bioinformatics 2008;3(3):142-148. |
R832721 (2008) |
Exit Exit |
|
|
Ovacik MA, Sukumaran S, Almon RR, DuBois DC, Jusko WJ, Androulakis IP. Circadian signatures in rat liver: from gene expression to pathways. BMC Bioinformatics 2010;11:540. |
R832721 (2008) R832721 (Final) |
Exit Exit Exit |
|
|
Ovacik MA, Androulakis IP. Enzyme sequence similarity improves the reaction alignment method for cross-species pathway comparison. Toxicology and Applied Pharmacology 2013;271(3):363-371. |
R832721 (2008) R832721 (Final) |
Exit Exit Exit |
|
|
Ovacik MA, Sen B, Euling SY, Gaido KW, Ierapetritou MG, Androulakis IP. Pathway modeling of microarray data: a case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP). Toxicology and Applied Pharmacology 2013;271(3):386-394. |
R832721 (Final) |
Exit Exit |
|
|
Piazza M, Feng X-J, Rabinowitz JD, Rabitz H. Diverse metabolic model parameters generate similar methionine cycle dynamics. Journal of Theoretical Biology 2008;251(4):628-639. |
R832721 (2008) |
Exit Exit Exit |
|
|
Rabinowitz JD, Hsiao JJ, Gryncel KR, Kantrowitz ER, Feng X-J, Li G, Rabitz H. Dissecting enzyme regulation by multiple allosteric effectors: nucleotide regulation of aspartate transcarbamoylase. Biochemistry 2008;47(21):5881-5888. |
R832721 (2008) |
Exit |
|
|
Rajgaria R, McAllister SR, Floudas CA. A novel high resolution Cα—Cα distance dependent force field based on a high quality decoy set. Proteins 2006;65(3):726-741. |
R832721 (2007) R832721 (Final) R832721C005 (2006) R832721C005 (2007) |
Exit Exit |
|
|
Rajgaria R, McAllister SR, Floudas CA. Distance dependent centroid to centroid force fields using high resolution decoys. Proteins: Structure, Function, Bioinformatics 2008;70(3):950-970. |
R832721 (2008) |
Exit |
|
|
Rajgaria R, McAllister SR, Floudas CA. Towards accurate residue-residue hydrophobic contact prediction for α helical proteins via integer linear optimization. Proteins: Structure, Function, Bioinformatics 2009;74(4):929-947. |
R832721 (2008) R832721 (Final) |
Exit |
|
|
Rajgaria R, Wei Y, Floudas CA. Contact prediction for beta and alpha-beta proteins using integer linear optimization and its impact on the first principles 3D structure prediction method ASTRO-FOLD. Proteins 2010;78(8):1825-1846. |
R832721 (Final) |
Exit |
|
|
Reschly EJ, Ai N, Ekins S, Welsh WJ, Hagey LR, Hofmann AF, Krasowski MD. Evolution of the bile salt nuclear receptor FXR in vertebrates. Journal of Lipid Research 2008;49(7):1577-1587. |
R832721 (2008) |
Exit Exit Exit |
|
|
Reschly EJ, Ai N, Welsh WJ, Ekins S, Hagey LR, Krasowski MD. Ligand specificity and evolution of liver X receptors. Journal of Steroid Biochemistry and Molecular Biology 2008;110(1-2):83-94. |
R832721 (2008) |
Exit |
|
|
Saharidis GK, Ierapetritou MG. Resolution method for mixed integer bi-level linear problems based on decomposition technique. Journal of Global Optimization 2009;44(1):29-51. |
R832721 (2008) |
Exit Exit |
|
|
Sasso AF, Isukapalli SS, Georgopoulos PG. A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals. Theoretical Biology and Medical Modelling 2010;7:17. |
R832721 (Final) |
Exit Exit Exit |
|
|
Sasso AF, Georgopoulos PG, Isukapalli SS, Krishnan K. Bayesian analysis of a lipid-based physiologically based toxicokinetic model for a mixture of PCBs in rats. Journal of Toxicology 2012;2012:895391, doi:10.1155/2012/895391. |
R832721 (2008) |
Exit Exit Exit |
|
|
Scheff JD, Almon RR, DuBois DC, Jusko WJ, Androulakis IP. A new symbolic representation for the identification of informative genes in replicated microarray experiments. OMICS–A Journal of Integrative Biology 2010;14(3):239-248. |
R832721 (Final) |
Exit |
|
|
Schnackenberg LK, Chen M, Sun J, Holland RD, Dragan Y, Tong W, Welsh W, Beger RD. Evaluations of the trans-sulfuration pathway in multiple liver toxicity studies. Toxicology and Applied Pharmacology 2009;235(1):25-32. |
R832721 (2008) |
Exit Exit Exit |
|
|
Stamatelos SK, Brinkerhoff CJ, Isukapalli SS, Georgopoulos PG. Mathematical model of uptake and metabolism of arsenic(III) in human hepatocytes – incorporation of cellular antioxidant response and threshold-dependent behavior. BMC Systems Biology 2011;5:16. |
R832721 (Final) |
Exit Exit Exit |
|
|
Sun JJ, Abdeljabbar DM, Clarke N, Bellows ML, Floudas CA, Link AJ. Reconstitution and engineering of apoptotic protein interactions on the bacterial cell surface. Journal of Molecular Biology 2009;394(2):297-305. |
R832721 (Final) |
Exit |
|
|
Tan MP, Smith EN, Broach JR, Floudas CA. Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures. BMC Bioinformatics 2008;9:268-289. |
R832721 (2008) |
Exit Exit Exit |
|
|
Taylor MS, Fung HK, Rajgaria R, Filizola M, Weinstein H, Floudas CA. Mutations affecting the oligomerization interface of G-protein-coupled receptors revealed by a novel de novo protein design framework. Biophysical Journal 2008;94(7):2470-2481. |
R832721 (2008) |
Exit Exit Exit |
|
|
Wang CY, Ai N, Arora S, Erenrich E, Nagarajan K, Zauhar R, Young D, Welsh WJ. Identification of previously unrecognized antiestrogenic chemicals using a novel virtual screening approach. Chemical Research in Toxicology 2006;19(12):1595-1601. |
R832721C004 (2006) R832721C004 (2007) |
not available |
|
|
Xue J, Zartarian V, Wang S-W, Liu SV, Georgopoulos P. Probabilistic modeling of dietary arsenic exposure and dose and evaluation with 2003-2004 NHANES data. Environmental Health Perspectives 2010;118(3):345-350. |
R832721 (Final) |
|
|
|
Yang EH, Almon RR, Dubois DC, Jusko WJ, Androulakis IP. Identification of global transcriptional dynamics. PLoS One 2009;10;4(7):e5992. |
R832721 (2008) |
Exit Exit Exit |
|
|
Yang E, Maguire T, Yarmush ML, Berthiaume F, Androulakis IP. Bioinformatics analysis of the early inflammatory response in a rat thermal injury model. BMC Bioinformatics 2007;8:10. |
R832721 (2007) |
|
|
|
Yang E, Simcha D, Almon RR, Dubois DC, Jusko WJ, Androulakis IP. Context specific transcription factor prediction. Annals of Biomedical Engineering 2007;35(6):1053-1067. |
R832721 (2007) |
Exit Exit |
|
|
Yang E, Foteinou PT, King KR, Yarmush ML, Androulakis IP. A novel non-overlapping bi-clustering algorithm for network generation using living cell array data. Bioinformatics 2007;23(17):2306-2313. |
R832721 (2007) |
Exit Exit |
|
|
Yang E, Maguire T, Yarmush ML, Androulakis IP. Informative gene selection and design of regulatory networks using integer optimization. Computers & Chemical Engineering 2008;32(4-5):633-649. |
R832721 (2007) R832721 (2008) |
Exit Exit |
|
|
Yang E, Maguire TJ, Yarmush ML, Berthiaume F, Androulakis IP. Identification of regulatory mechanisms of the hepatic response to thermal injury. Computers & Chemical Engineering 2008;32(1-2):356-369. |
R832721 (2007) R832721 (2008) |
Exit Exit |
|
|
Yang E, Almon RR, DuBois DC, Jusko WJ, Androulakis IP. Extracting global system dynamics of corticosteroid genomic effects in rat liver. Journal of Pharmacology and Experimental Therapeutics 2008;324(3):1243-1254. |
R832721 (2007) R832721 (2008) |
Exit Exit Exit |
|
|
Yang E, Androulakis IP. Assessing and selecting gene expression signals based upon the quality of the measured dynamics. BMC Bioinformatics 2009;10:55-67. |
R832721 (2008) |
Exit Exit Exit |
|
|
Yang E, Yarmush ML, Androulakis IP. Transcription factor network reconstruction using the living cell array. Journal of Theoretical Biology 2009;256(3):393-407. |
R832721 (2008) |
Exit Exit Exit |
|
|
Yang H, Roth CM, Ierapetritou MG. A rational design approach for amino acid supplementation in hepatocyte culture. Biotechnology and Bioengineering 2009;103(6):1176-1191. |
R832721 (2008) R832721 (Final) |
Exit Exit |
|
|
Yang H, Ierapetritou MG, Roth CM. Effects of amino acid transport limitations on cultured hepatocytes. Biophysical Chemistry 2010;152(1-3):89-98. |
R832721 (2008) R832721 (Final) |
Exit |
|
|
Yang H, Roth CM, Ierapetritou MG. Analysis of amino acid supplementation effects on hepatocyte cultures using flux balance analysis. OMICS 2011;15(7-8):449-460. |
R832721 (2008) |
Exit |
|
|
Yang Y, Xu X, Georgopoulos PG. A Bayesian population PBPK model for multiroute chloroform exposure. Journal of Exposure Science & Environmental Epidemiology 2010;20(4):326-341. |
R832721 (2008) R832721 (Final) |
Exit |
Supplemental Keywords:
computational toxicology, bioinformatics, proteomics, metabonomics, physiomics, cytomics, genomics, transcriptomics, enviroinformatics, cheminformatics, biologically based dose response-modeling, cross-species extrapolation, risk assessment,, Health, Scientific Discipline, Geographic Area, State, Risk Assessments, Biochemistry, Environmental Monitoring, Biology, ecological risk assessment, computational toxicology, toxicology, biopollution, dose-response, environmental risks, outreach and training, chemical composition, New Jersey (NJ), human exposure, bioinformatics, human health riskProgress and Final Reports:
2006 Progress Report2007 Progress Report
2008 Progress Report
Final Report
Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R832721C001 Development and Application of the DORIAN (Dose-Response Information Analysis) System
R832721C002 Hepatocyte Metabolism Model for Xenobiotics
R832721C003 Development of Computational Tools for Optimal Identification of Biological Networks
R832721C004 Cheminformatics Tools for Toxicant Characterization
R832721C005 Optimization Tools for In Silico Structural Proteomics


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface ParseDerivation
| Method Summary | |
|---|---|
java.util.Collection<Element> |
deleteFirstAndLast(java.util.Collection<Element> cl)
Delete the first and last Elements of the Collection and returns a new Collection without those Elements. |
java.util.Collection<java.util.Collection<Element>> |
splitElementsBeforeToken(java.util.Collection<Element> cl,
java.lang.String tk)
Given a Collection of Elements and a token tk, the function splits the Collection in severals subcollections in the following way: 1) If for example the Collection is cl = abcTKdeTKa, and the token is TK, the function splits cl in: "abc", "de" and "a". 2) If for example the Collection is cl = TKabc, and the token is TK, the function splits cl in: NULL. 3) If for example the Collection is cl = TKabcTK, and the token is TK, the function splits cl in: "abc". 4) If for example the Collection is cl = abc, and there isn't a token, the function splits cl in: NULL. |
java.util.Collection<java.util.Collection<java.util.Collection<Element>>> |
splitElementsBetweenTokens(java.util.Collection<Element> cl,
java.lang.String tk1,
java.lang.String tk2)
Given a Collection of Elements and the tokens tk1 and tk2, the function splits the Collection in severals pairs of subcollections in the following way: 1) If for example the Collection is cl = TK1abcTK2deTK1geTK2hf, and the tokens are TK1 and TK2, the function splits cl in: {"abc" , "de"} and {"ge", "hf"}. 2) If for example the Collection is cl = TK1abcTK2, and the tokens are TK1 and TK2, the function splits cl in: {"abc" , NULL}. 3) If for example the Collection is cl = abcTK1ggTK2rr, and the tokens are TK1 and TK2, the function splits cl in: {"gg" , "rr"}. |
| Method Detail |
|---|
java.util.Collection<java.util.Collection<Element>> splitElementsBeforeToken(java.util.Collection<Element> cl, java.lang.String tk)
cl
- The Collection to be splited.tk
- The token to be used in order to split the Collection.
java.util.Collection<java.util.Collection<java.util.Collection<Element>>> splitElementsBetweenTokens(java.util.Collection<Element> cl, java.lang.String tk1, java.lang.String tk2)
cl
- The Collection to be splitedtk1
- The first token to be used in order to split the Collection.tk2
- The first token to be used in order to split the Collection.java.util.Collection<Element> deleteFirstAndLast(java.util.Collection<Element> cl)
cl
- The Collection from whom the first and last Elements are deleted.
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Bolton Muslim Girls School can expand to take extra 150 pupils
It's already the best-performing school in the district
by Joseph Timan, Local Democracy ReporterThe best-performing school in Bolton is set to expand by 150 pupils over the next five years as plans for its future have been approved.
Bolton Muslim Girls School has been granted planning permission to build a four-storey side extension.
The school, which will increase its student numbers from 600 to 750, can now also use the second and third floors of the mill building it is located in for educational purposes.
The expansion will allow the school to add design and technology as well as drama to its curriculum.
Work at the site is due to start in January and an additional intake of 30 pupils per year is planned.
Deputy head Helen Andiyapan warned delays to the expansion of the “oversubscribed” school would put £2.2m of funding at risk.
She said: “There will be a local shortage of places if this expansion does not go ahead. We are aware of the concerns raised and have tried our utmost to address these in the best nature possible.”
The planning committee approved the application last week despite residents raising concerns about increased traffic in the area.
Hanif Kola spoke on behalf of residents objecting to the proposal at a town hall meeting on Thursday.
He said that residents had tried to be fair and take a “balanced” approach with the school, but concerns had “fallen on deaf ears”.
They asked for each class to have an assigned entrance to ease congestion and demanded this becomes school policy so that it can be enforced.
He said: “We support the school and its efforts to expand its teaching provision but to have one access and entry point for a further 150 students is a major health and safety issue for the school, medical centre and the residents which cannot be compromised or overlooked in any way.”
Rumworth councillor Shamim Abdullah, who requested that the planning committee discusses the plans and makes the final decision, said that residents in her ward felt that the roads around the school cannot cope with traffic as it is.
However, she was satisfied that the school had taken appropriate measures to mitigate these problems.
Cllr Elaine Sherrington said: “The difficulty with the school is the fact that it is in an old mill. It was never designed to be a school and it’s in one of the most built up areas in the town.
“At the end of the day, the school is where it is and there’s nothing we can do about that.
Want more news from Bolton? Here's where you can find it.
We now have a dedicated Facebook page bringing you all the latest news, events and community news in Bolton.
To keep up to date with all that is happening in Bolton - and to join in the discussion - follow the page here.
Reporter Tom George covers all things Bolton for the Manchester Evening News, you can follow him on Twitter here.
“I think if we talk about expansion in the future, I don’t think we can go over five-storeys.
“At that stage I think they would have to look at a brand new site.”
Plans were passed unanimously.


about me
Hi! My name is Rosa Swaby and I am a Computer Science student at NYU - College of Arts and Science. I am originally from Georgia and I have been living in NYC for 2 years. I enjoy working on web developing and design and I hope to be able to be a web developer / designer in the future.
I am also really into music, dance and singing. Recently I have been listening to Lemonade (BEYONCE), and I definitely recommend it! I really enjoy eating as well, so if you want to check out some cool places in the city to eat, or just want to hang out, I am definitely in. Check out my resume below and send me a message if you want to chat!
skills
Computer Science
-
Java
-
Data Structures
-
Python
-
C
Web Developing
-
HTML/CSS
-
JQuery
-
MySQL
-
PHP
-
MongoDB
Graphic Design
-
Photoshop
-
InDesign
Miscellaneous
-
Final Cut Pro
-
iPhoto
-
Adobe Premiere
-
AutoCAD
Computer Science
-
Java
-
Data Structures
-
Python
-
C
Web Developing
-
HTML/CSS
-
JQuery
-
MySQL
-
PHP
-
MongoDB
Graphic Design
-
Photoshop
-
InDesign
Miscellaneous
-
Final Cut Pro
-
iPhoto
-
Adobe Premiere
-
AutoCAD
contact
Thanks for checking out my page! Make sure to check out my resume and if you would like to contact me, you can reach me by contacting me via my social media or emailing me directly at<EMAIL_ADDRESS>Bye!


Only contains instructions from the first half of this MIPS Reference Data that is in the CS2100 syllabus.
For branch and jump instructions, use the actual immediate field.
Both decimal and hexadecimal numbers can be used for the immediate field. Numbers appended with "0x" will be treated as hexadacimal numbers, otherwise, they will be treated as decimal numbers.


Toggle navigation
Caesar cipher
Text to process
(Please enter some text)
Right shift
Encode
Decode
Result


Time and Habits
The first couple of links talked about meditation and mindfulness. Meditation doesn't seem that interesting for me, a few of the links were too pseudosciencey for my liking and although it may be useful for many people, it doesn't tend to work for me. One of the lines stood out:
Many people will tell you that allowing time and space to listen to your emotions, listen to your heart and just be mindful is either a waste of time or somehow ‘hippy psychobabble’.
I concur.
The Pomodoro Technique I have come across before. The video is nice and catchy, but I'll be honest: I can't really understand exactly how it all works. I also don't own a tomato timer, so I think that this method may not be ideal for me.
The article 'Making it big by starting small' I really liked, and found that a lot of it resonated with me. Small, incremental steps is how I ever accomplish anything.
The video on habits also resonated with me. Chocolate sounds like a great motivator to get me to go to the gym, even if there is a slight canceling effect that occurs when the chocolate is consumed. It also presented the idea of small increments to build the foundations for a longer-lasting habit. It suggested that practice is not necessarily always fun; sometimes if you want to achieve a desired result, you must bite the bullet and do the hard yards. Of course, how hard the yards are will differ from person to person, and this idea was also suggested in the video with the notion that there are morning people and night people, which resonated with me because I am certainly not a morning person.


Class JobManager
JobManager
- Native5\Api\ApiClient
- Native5\Services\Job\JobManager
Namespace: Native5\Services\Job
Package: Native5\Services\Jobs
Category: Jobs
Copyright: 2012 Native5. All Rights Reserved
License: attached NOTICE.md for details
Author: Shamik Datta<EMAIL_ADDRESS>Version: Release: 1.0
Link: http://www.docs.native5.com
Located at Native5/Services/Job/JobManager.php
Package: Native5\Services\Jobs
Category: Jobs
Copyright: 2012 Native5. All Rights Reserved
License: attached NOTICE.md for details
Author: Shamik Datta<EMAIL_ADDRESS>Version: Release: 1.0
Link: http://www.docs.native5.com
Located at Native5/Services/Job/JobManager.php
Methods summary
public
|
|
public
boolean
|
|
public
|
|
public
|
|
public
|
|
public
|
|
public
@see
|
Magic methods summary
Constants summary
string |
API_PATH
|
'job/' |
|
string |
CREATE_JOB
|
'create/' |
|
string |
GET_JOB
|
'' |
|
string |
UPDATE_JOB_STATE
|
'state/' |
|
string |
UPDATE_JOB_STATUS
|
'status/' |
|
string |
SET_JOB_RESULT
|
'result/' |
|
string |
DELETE_JOB
|
'delete/' |


virus mPTP clusters genotypes HCV HBV hepatitis species classification {border-style delimitation px;} #ffffff;} genetic genotype phylogenetic using barcoding MCMC clustering data methods ABGD sampling sequence subtypes viral viruses (Fig. analysis current model speciation taxonomic tool delimited number support taxonomy DNA additional branches identification identified information new node obtained px; sequences {font-family (i.e., Fig. S). biodiversity corresponding distance-based divergence font-size intraspecific threshold value HBV, National and, dataset different double; evolution gap inferred minimum numbers red samples set substantially thresholds used (Simmonds Click HCV, LINK approved authored automated available based border-color border-width cluster colored currently data, distance draft. drafts file. final genome genotypes, indicate indicated input life maximum method paper, parameters provided reviewed seven shows solid; split study {font-style {font-weight <. (e.g., (support .). ./peerj./supp-Figure Academy Appendix Comparison Raw Sciences Simmonds Smith States United acknowledged applied appropriate black bold clusters, comprises computational courier; deployed distribution diversity em; given global human lack large lower mPTP, model. molecular origin output particular phylogeny potential previously prior pt;} relationships response sampled second sequencing shown, subgenotypes time treatment tree virus, yielded


The Server Status dialogue displays the current connections to each database, the user that is connected, the process ID, the client address and start time (on PostgreSQL 8.1 and above), the current query being executed (if any), and the query start time (where appropriate) on PostgreSQL 7.4 and above on the Status tab.
The Cancel button allows cancelling the query running on a specific backend. Terminate will shutdown the backend. Attention: Both functions should be used carefully, as the interrupt the client’s work ungracefully. Particularly, the terminate function might disturb the function of the complete server, force it to restart its services and thus interrupt all user connections. You should use this function only if the server is seriously injured by a backend you can’t control otherwise.
The Locks tab shows the current locks outstanding in the PostgreSQL Lock Manager. This information can be useful when attempting to debug or track down deadlocks on your server. Not all information is necessarily shown for each lock. In particular, the Relation name may be shown as an OID instead of by it’s name, if the relation is in a different database to that being monitored.
Note: When the pg_locks view is accessed as is the case whenever this dialgue is open, PostgreSQL’s internal lock manager data structures are momentarily locked, and a copy is made for the dialogue to display. This ensures that the dialogue displays a consistent set of results, while not blocking normal lock manager operations longer than necessary. Nonetheless there could be some impact on database performance if this view is read often.
On a PostgreSQL server running version 8.1 or newer, the Transaction tab allows you to view outstanding prepared transactions. Prepared transactions are an aspect of Two Phase Commit (2PC), used in distributed transaction managers. Usually, prepared transactions are handled by the transaction manager. In case of a failure, it might be necessary to commit or rollback a transaction manually; you can use the ‘Commit’ or ‘Rollback’ buttons to do this.
The Logfile tab shows server log files, if configured in postgresql.conf (redirect_stderr or logging_collector = true, log_destination = ‘stderr’ and log_filename = ‘postgresql-%Y-%m-%d_%H%M%S.log’ on PostgreSQL or ‘enterprisedb-%Y-%m-%d_%H%M%S.log’ on EnterpriseDB’s Advanced Server). pgAdmin will extract a time stamp from the logfile in a separate column, if the log_line_prefix is configured accordingly. We recommend using ‘%t:’ as format, because more complicate formats might not be interpretable correctly.
The combobox allows you to select historic logfiles or the current one. If “current” is selected, pgAdmin will correctly detect logfile rotation and continue to display them.
The “Rotate” button will force the server to rotate its server logfile. This function is currently not implemented on 8.0 servers; if you think this is valuable for you please contact us.
Please note that displaying the logfile requires additional functions loaded on the server side, which are available for 8.x servers only.
To refresh the display click the Refresh button. The display will also be automatically refreshed based on the refresh interval specified. Note that you have one refresh rate per tab.
You can hide panes by clicking on their close button or by clicking on the appropiate menu item in the View menu.
You can also copy some lines on the tabs’ list. Select the lines you want to copy and click on the Copy button of the toolbar.


{% load i18n %}
{% trans "Dear" %} {{ subscription.email }},
{% trans "Thank you for subscribing to our newsletter." %}
{% trans "Please click the following link to verify your subscription." %}
https://{{ request.get_host}}{% url "newsletter_verify" uuid=subscription.verification_token %}
{% trans "If you did not subscribe to our newsletter, you can just ignore this email. The subscription is only active, when it has been verified." %}
{% trans "Regards" %}


com.intel.analytics.zoo.models
Trait for Ranking models (e.g., TextMatcher and Ranker) that provides validation methods with different metrics.
The base class for models in Analytics Zoo.
Input data type.
Output data type.
Numeric type of parameter(e.g. weight, bias). Only support float/double now.
The base class for models in Analytics Zoo.
Input data type.
Output data type.
Numeric type of parameter(e.g. weight, bias). Only support float/double now.


Opal, the Application Wrapper Web service, provides a way to wrap up existing scientific applications rapidly as Web services, and expose them to various clients. The implementation provides features such as scheduling (e.g. using Condor/SGE via Globus or DRMAA) and security (using GSI-based certificates), Furthermore, the service provides job and data management (by executing every job in a separate working directory), and state management (by storing the service state in a PostgreSQL database). The application developer specifies a configuration for a scientific application and deploys the application as a service following a small sequence of steps. End-users can now access this application remotely using the WSDL of the service.
The WSDL for the service is defined inside wsdl/opal.wsdl. Stub generators provided by Web service toolkits are then used to generate the client and server-side bindings for the services. In our case, the services are implemented in Java using the Apache Axis toolkit, while the clients can be in any language.
The WSDL defines operations to do the following:
The source distribution can be used to install both the server and the client sides on Unix and Windows platforms. The prerequisites for the client and server installations are as follows.
Apart from the above packages required for the client, the server also requires the following packages:
The following packages are optional:
We have used Condor for serial jobs only, and SGE for serial as well as parallel jobs. Globus jobmanager plugins are available for both of the above, and must be installed if you plan to use either of them.
Another alternative to access schedulers is via the DRMAA API. The Web services can submit jobs to schedulers as long as they support the DRMAA API. We have only tested job submits to SGE via DRMAA.
Download the source distribution for installation from here, if you don't have the appropriate version already.
Extract the downloaded tarball using the GNU tar utility (or other
similar utilities for Windows), as follows:
tar zxvf opal-ws-1.5.1.tar.gz
This should create a new directory called opal-ws-1.5.1/ where all the sources are expanded. Henceforth, we refer to this directory as OPAL_HOME.
1. Install Axis inside Tomcat by copying over the
$AXIS_HOME/webapps/axis directory to $CATALINA_HOME/webapps. On Windows,
you can use Windows Explorer to do the same, while on Unix you can execute
the following command:
cp -r $AXIS_HOME/webapps/axis $CATALINA_HOME/webapps
2. Edit $OPAL_HOME/etc/opal.properties to configure the static container
properties correctly. It should look something like the following:
# the base URL for the tomcat installation
# this is required since Java can't figure out the IP
# address if there are multiple network interfaces
tomcat.url=http://localhost:8080
# parallel parameters
num.procs=1
mpi.run=/Users/sriramkrishnan/Misc/mpich-1.2.7/bin/mpirun
# location of working directory relative to $CATALINA_HOME/webapps.
# this could be a symbolic link to another location (which should be
# NFS mounted if this is on a cluster). if this is a symlink, copy
# etc/opal.xml to $CATALINA_HOME/conf/Catalina/localhost/opal.xml. if
# the name of the symlink is changed to something other than "opal",
# modify the opal.xml accordingly
# working.dir=opal
# database information
database.use=false
database.url=jdbc:postgresql://localhost/app_db
database.user=app_user
database.passwd=app_passwd
# drmma information
drmaa.use=false
drmaa.pe=mpich
# globus information
globus.use=false
globus.gatekeeper=localhost:2119/jobmanager-sge
globus.service_cert=/Users/sriramkrishnan/certs/app_service.cert.pem
globus.service_privkey=/Users/sriramkrishnan/certs/app_service.privkey
Set the tomcat.url to the correct http://ip-address:port of the server. If the service will wrap a parallel application, set the num.procs to the number of processors available, and the mpi.run to the location of the mpirun on your host.
By default, all new working directories for job executions are created
inside the $CATALINA_HOME/webapps/ROOT directory. You may wish to change
this to another location on your system (which should be NFS mounted, if
you are installing on a cluster). If you would like to do so for any
reason, uncomment the property working.dir. Then run the following
commands:
cp $OPAL_HOME/etc/opal.xml $CATALINA_HOME/conf/Catalina/localhost/
cd $CATALINA_HOME/webapps
ln -s /path/to/working_dir/on/nfs opal
Note that the above use of symbolic links will only work on Unix systems.
If you wish to install a database to persist service state, please refer to database.html. If you would like to set up scheduler support, refer to scheduler.html. You can also optionally set up secure access to your services by consulting security.html.
3. Edit the $OPAL_HOME/build-opal.properties file to ensure that the build properties are set correctly. Set catalina.home to point to the location of your Tomcat installation (i.e. $CATALINA_HOME), axis.webapp to the name used by the Axis web application (typically, it is just axis), and tomcat.port to the port number that the Tomcat server is running on.
4. Install the Opal jars into the Axis webapp, by executing the
following command:
ant -f build-opal.xml install
5. Run the Tomcat server by changing to the $CATALINA_HOME/bin directory,
and running the appropriate command (bat on Windows, sh on Unix):
./startup.bat|sh
6. Validate that Axis has been deployed correctly by clicking on http://localhost:8080/axis/happyaxis.jsp. If you have deployed Tomcat on another port, you will have to change the port number above. If all the Needed Components are found, Axis has been deployed fine. You can ignore the warnings about the Optional Components.
7. Create a configuration file for your application. For example, you
can download the Babel
program, which is designed to support molecular modeling, chemistry, and
many related areas, including interconversion of file formats and data. A
sample configuration file for the same, located in
$OPAL_HOME/etc/babel_config.xml, is shown below.
<appConfig xmlns="http://nbcr.sdsc.edu/opal/types"
xmlns:xsd="http://www.w3.org/2001/XMLSchema">
<metadata>
<usage><![CDATA[./babel [-i<input-type>] <name> [-o<output-type>] <name>]]></usage>
<info xsd:type="xsd:string">
<![CDATA[
...
Currently supported input types
alc -- Alchemy file
prep -- Amber PREP file
...
Currently supported output types
...
caccrt -- Cacao Cartesian file
cacint -- Cacao Internal file
...
Additional options :
...
]]>
</info>
</metadata>
<binaryLocation>/Users/sriramkrishnan/bin/babel</binaryLocation>
<defaultArgs></defaultArgs>
<parallel>false</parallel>
</appConfig>
The configuration consists of a top level element appConfig, which contains metadata, binaryLocation, defaultArgs, and parallel elements. The metadata consists of usage, which is a string specifying how the application is to be invoked, and an array of optional application information specified as info elements. In the above file, the various options that can be used with the application are specified within the metadata. The binaryLocation specifies the location of the application binary - note that this has to be the location of a single executable. No arguments may be specified here. However, default arguments that need to be used for every run can be specified inside the defaultArgs element. The parallel element specifies if an application is parallel or not. Use the babel_config.xml as a guideline to write configurations for your particular applications.
8. Deploy the services inside Tomcat, by changing to the $OPAL_HOME
directory, and running the following command:
$ANT_HOME/bin/ant -f build-opal.xml deploy -DserviceName=<serviceName> -DappConfig=<appConfig>
For example, to deploy the Babel service, you would type the following
command:
$ANT_HOME/bin/ant -f build-opal.xml deploy -DserviceName=BabelServicePort -DappConfig=etc/babel_config.xml
Note that you can undeploy your service at any time by running the
following command:
$ANT_HOME/bin/ant -f build-opal.xml undeploy -DserviceName=<serviceName>
If you plan on using the service with large inputs and outputs, it is a good idea to increase the heap size being used by the JVM. This can be done by setting the JAVA_OPTS environment variable to -Xmx1024m, and restarting Tomcat. This increases the heap size to 1GB. If all went well until this step, the services are running and ready to be used. Test them by running the client, described in the following section.
The service creates new working directories for every execution. These working directories are not deleted automatically, so they must be periodically cleaned up. You may use the script $OPAL_HOME/etc/cleanup.sh to do so - you will have to modify it to point to your Tomcat installation (and optionally modify the number of days to retain scratch directories).
A generic Java client is implemented by $OPAL_HOME/src/edu/sdsc/nbcr/opal/GenericServiceClient.java. It lets you run any application exposed as an Opal service, and retrieve its status and outputs.
To compile the client, perform the following step from inside
the $OPAL_HOME directory.
$ANT_HOME/bin/ant -f build-opal.xml jar
Before running the client, set your classpath using the
classpath.bat|(c)sh script depending on the OS/shell you use - e.g. if you
use tcsh on Unix, set your classpath by typing the following command:
source classpath.csh
To launch a job using the Babel service which was described above, you could use the
following command, which displays the resulting job id, along with the preliminary status.
java edu.sdsc.nbcr.opal.GenericServiceClient -l http://localhost:8080/axis/services/BabelServicePort
-r launchJob
-a "-ipdb sample.pdb -h -opdb output.pdb"
-f etc/sample.pdb
You can retrieve job status by running the following command:
java edu.sdsc.nbcr.opal.GenericServiceClient -l http://localhost:8080/axis/services/BabelServicePort
-r queryStatus
-j <job_id>
Once the job has finished executing, you can also retrieve output metadata using:
java edu.sdsc.nbcr.opal.GenericServiceClient -l http://localhost:8080/axis/services/BabelServicePort
-r getOutputs
-j <job_id>
You may need to change the above URL if you used a different port, or are
running the client from another machine. Note that you can get the complete
usage information for the client by using the following command:
java edu.sdsc.nbcr.opal.GenericServiceClient
To report bugs and feature requests, please use the NBCR Web Services User Forum (WSUF).


{% extends "manage/base.html" %} {% import "bootstrap/wtf.html" as wtf %} {% import "manage/_macros.html" as macros %} {% block main_body %}
没有结果


{#Insert this html into the page you want to track to flag mouse movements and clicks (i.e. help with bot detection)#}


Raven air©Inspired by Raven Industries
Parameter index
The GHP-417, representing General Unmanned Helicopter Platform, can fly day-after-day, night-after-night, in adverse weather conditions, for up to 4 hours with max payload 130 kg at a time, on an accurate flight path under computer control.
Application scenarios
The GHP-417 is substantially safer than a full sized helicopter since it can auto rotate to the ground in a controlled landing with a complete failure of the main engine. Although full size helicopters may be able to perform this function with a highly skilled pilot, it often results in significant damage to the aircraft as well as injury to the pilot.
Product advantage
The GHP-417 is substantially safer than a full sized helicopter since it can auto rotate to the ground in a controlled landing with a complete failure of the main engine. Although full size helicopters may be able to perform this function with a highly skilled pilot, it often results in significant damage to the aircraft as well as injury to the pilot.
Strategic cooperation
GHP-417 can fly safely at low altitudes to provide a variety of inspection functions such as; pipelines, IEDs, railways, etc. GHP-417 updates a server computer in real time in flight, allowing users to view the latest information, via the Internet from any terminal designated by the operators.


Exodus 13:22
He took not away the pillar of the cloud by day, nor the pillar of fire by night, from before the people.


Annotations to supercharge your vert.x development
ProjectCastle is well under way. Part of it, the part talking to Domino, is written in Java8 and vert.x. With some prior experience in node.js development vert.x will look familiar: base on event loop and callbacks, you develop in a very similar way. The big differences: vert.x runs on the JVM8, it is by nature of the JVM multi-threaded, features an event bus and is polyglot - you can develop in a mix of languages: Java, JavaScript, Jython, Groovy etc.
This post reflects some of the approaches I found useful developing with vert.x in Java. There are 3 components which are core to vert.x development:
Java annotations to the rescue! If you are new to annotations, go and check out this tutorial to get up to speed. For my project I defined three of them, with one being able to be applied multiple times.
and the repeatability annotation (new with Java8):
Since traversing all classes is expensive, we have one method that does that once calling the 3 different annotation processors once for each class
Left as an exercise to the reader: runs the analysis at compile time instead of runtime.
As usual: YMMV
This post reflects some of the approaches I found useful developing with vert.x in Java. There are 3 components which are core to vert.x development:
-
Verticle
A unit of compute running with an event loop. Usually you start one Verticle (optional with multiple instances) as your application, but you might want/need to start additional ones for longer running tasks. A special version is the worker verticle, that runs from a thread pool to allow execution of blocking operations -
EventBus
The different components of your application message each other via the EventBus. Data send over the EventBus can be a String, a JsonObject or a buffer. You also can send any arbitrary Java class as message once you have defined a codec for it -
Route
Like in node.js a vert.x web application can register routes and their handlers to react on web input under various conditions. Routes can be defined using URLs, HTTP Verbs, Content-Types ( for POST/PUT/PATCH operations)
Java annotations to the rescue! If you are new to annotations, go and check out this tutorial to get up to speed. For my project I defined three of them, with one being able to be applied multiple times.
CastleRequest
A class annotated with CastleRequest registers its handler with the EventBus, so the class can be sent over the EventBus and get encoded/decode appropriately. A special value for the annotation is "self" which indicates, that the class itself implements the MessageCodec interface
@Documented
@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.TYPE})
public @interface CastleRequest {
// We use value to ease the syntax
// to @CastleRequest(NameOfCodec)
// Special value: self = class implements the MessageCodec interface
String value();
}
CastleRoute
This annotation can be assigned multiple times, so 2 annotation interfaces are needed
@Documented
@Repeatable(CastleRoutes.class)
@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.TYPE})
public @interface CastleRoute {
String route();
String description();
String mimetype() default "any";
String method() default "any";
}
and the repeatability annotation (new with Java8):
@Documented
@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.TYPE})
public @interface CastleRoutes {
CastleRoute[] value();
}
CastleVerticle
Classes marked with this annotation are loaded as verticles. They can implement listeners to the whole spectrum of vert.x listening capabilities
@Documented
@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.TYPE})
public @interface CastleVerticle {
String type() default "worker";
int instances() default 0;
boolean multithreaded() default false;
}
Loading it all
With a little glue code (see below), all Verticles, Routes and Codecs get loaded by looking up the annotations. You add a new file or remove one: no additional action is required.Since traversing all classes is expensive, we have one method that does that once calling the 3 different annotation processors once for each class
private void loadClassesByAnnotation(final Router router) {
try {
// Get the classes from the current loader to check for more
final ClassPath classPath = ClassPath.from(this.getClass().getClassLoader());
// Extract the package name from the full class name
String packageName = this.getClass().getName();
packageName = packageName.substring(0, packageName.lastIndexOf("."));
// Get all classes in this tree
for (final ClassInfo classInfo : classPath.getTopLevelClassesRecursive(packageName)) {
@SuppressWarnings("rawtypes")
final Class candidate = classInfo.load();
this.loadVerticleByAnnotation(candidate);
this.loadCodecByAnnotation(candidate);
this.loadRouteByAnnotation(candidate);
}
} catch (IOException e) {
this.logger.error(e);
}
}
@SuppressWarnings({ "rawtypes", "unchecked" })
private void loadCodecByAnnotation(final Class candidate) {
EventBus eventBus = this.vertx.eventBus();
final Annotation[] annotation = candidate.getAnnotationsByType(CastleRequest.class);
// Registering all Codecs
for (int i = 0; i < annotation.length; i++) {
try {
final CastleRequest cr = (CastleRequest) annotation[i];
final String codecClassName = cr.value();
Object codecCandidate;
if (codecClassName.equalsIgnoreCase("self")) {
// The object contains its own message codec
codecCandidate = candidate.newInstance();
} else {
codecCandidate = Class.forName(codecClassName).newInstance();
}
if (codecCandidate instanceof MessageCodec) {
MessageCodec messageCodec = (MessageCodec) codecCandidate;
eventBus.registerDefaultCodec(candidate, messageCodec);
} else {
this.logger.error("Class with CastleRequest Annotation has wrong codec type:" + codecClassName);
}
} catch (InstantiationException | IllegalAccessException | ClassNotFoundException e) {
this.logger.error(e);
}
}
}
@SuppressWarnings({ "unchecked", "rawtypes" })
private void loadRouteByAnnotation(final Class candidate) {
final Annotation[] annotation = candidate.getAnnotationsByType(CastleRoute.class);
for (int i = 0; i < annotation.length; i++) {
try {
final CastleRoute cr = (CastleRoute) annotation[i];
// We got a class that shall be used as a router
if (CastleRouteHandler.class.isAssignableFrom(candidate)) {
// If a class has multiple routes assigned we might load them more
// than once but that's acceptable
final Class
toBeloaded = candidate;
CastleRouteHandler crh = toBeloaded.newInstance();
// Finally initialization and recording in our list
crh.init(this.vertx, router, cr.method(), cr.route(), cr.mimetype(), cr.description());
this.routeList.put(cr.route(), cr.description());
this.routeHandlers.add(crh);
} else {
this.logger.error("Class with CastleRouter Annotation has wrong type:" + candidate.getName());
}
} catch (InstantiationException | IllegalAccessException e) {
this.logger.error(e);
}
}
}
@SuppressWarnings({ "rawtypes", "unchecked" })
private void loadVerticleByAnnotation(final Class candidate) {
final Annotation[] annotation = candidate.getAnnotationsByType(CastleVerticle.class);
for (int i = 0; i < annotation.length; i++) {
if (Verticle.class.isAssignableFrom(candidate)) {
final CastleVerticle cv = (CastleVerticle) annotation[i];
final String verticleID = candidate.getName();
final DeploymentOptions options = new DeploymentOptions();
if (cv.type().equalsIgnoreCase("worker")) {
options.setWorker(true);
}
// Overwrite the instances if number is specified
if (cv.instances() > 0) {
options.setInstances(cv.instances());
}
options.setMultiThreaded(cv.multithreaded());
this.vertx.deployVerticle(verticleID, options, result -> {
if (result.succeeded()) {
this.logger.info(verticleID + " started as " + result.result());
this.localVerticles.add(result.result());
} else {
this.logger.error(result.cause());
}
});
} else {
this.logger.error("Class with CastleVerticle Annotation has wrong type:" + candidate.getName());
}
}
}
public interface CastleRouteHandler {
public String getDescription();
// Return the actual route
public String getRoute();
// The methods that needs to be overwritten in each instance
// One for each method we do support
public void handleDelete(final RoutingContext ctx);
public void handleGet(final RoutingContext ctx);
public void handleHead(final RoutingContext ctx);
public void handleOptions(final RoutingContext ctx);
public void handlePost(final RoutingContext ctx);
public void handlePut(final RoutingContext ctx);
public void handlePatch(final RoutingContext ctx);
// initialize the actual route
public AbstractCastleRouteHandler init(final Vertx vertx, final Router router, final String method, final String route, String mimetype, String description);
}
public AbstractCastleRouteHandler init(final Vertx vertx, final Router router, final String method, final String route,
final String mimetype, final String description) {
this.vertx = vertx;
this.description = description;
this.route = route;
this.logger.info("Loading " + this.getClass().getName() + " for " + this.getRoute() + " .. " + description);
Route localRoute = null;
if ("any".equalsIgnoreCase(method) || "GET".equalsIgnoreCase(method)) {
localRoute = router.get(route).handler(this::handleGet);
}
if ("any".equalsIgnoreCase(method) || "POST".equalsIgnoreCase(method)) {
localRoute = router.post(route).handler(this::handlePost);
}
if ("any".equalsIgnoreCase(method) || "PUT".equalsIgnoreCase(method)) {
localRoute = router.put(route).handler(this::handlePut);
}
if ("any".equalsIgnoreCase(method) || "PATCH".equalsIgnoreCase(method)) {
localRoute = router.put(route).handler(this::handlePatch);
}
if ("any".equalsIgnoreCase(method) || "DELETE".equalsIgnoreCase(method)) {
localRoute = router.delete(route).handler(this::handleDelete);
}
if (localRoute != null && !"any".equalsIgnoreCase(mimetype)) {
localRoute.consumes(mimetype);
}
// Methods that need to be always available
router.options(route).handler(this::handleOptions);
router.options(route).handler(this::handleHead);
return this;
}
Left as an exercise to the reader: runs the analysis at compile time instead of runtime.
As usual: YMMV
Posted by Stephan H Wissel on 02 April 2016 | Comments (0) | categories: vert.x


CartoDB
Sewer Network
This demo shows a point an a line table from CartoDB, sewer lines and man holes. The man holes are displayed using a simple symbology while the sewer lines use the range symbology. Pipes up to 8" in diameter are shown with a thinner green line, while larger pipes are shown with a thicker orange line.
We're also using the singlePopup
option here so that only one Popup is shown for each layer. This keeps the map from getting cluttered when selecting lots of features.
cartodb_sewer_line = new lvector.CartoDB({ user: "geojason", table: "sewer_line", scaleRange: [15, 20], symbology: { type: "range", property: "pipe_dia", ranges: [ { range: [0, 8], vectorOptions: { weight: 4, color: "#46461f", opacity: 0.8 } },{ range: [8.00001, 100], vectorOptions: { weight: 8, color: "#ff7800", opacity: 0.8 } } ] }, popupTemplate: '

Sewer Line

Diameter	{pipe_dia} in.

Material	{pipe_mat}

Flows To	{wwtp} WWTP

', singlePopup: true }); var customMarker = L.Icon.extend({ options: { iconUrl: "../../docs-demo/img/markers/manhole.png", shadowUrl: null, iconSize: new L.Point(16, 16), iconAnchor: new L.Point(8, 8), popupAnchor: new L.Point(1, -8) } }); cartodb_man_hole = new lvector.CartoDB({ user: "geojason", table: "man_hole", scaleRange: [16, 20], symbology: { type: "single", vectorOptions: { circleMarker: true, radius: 20 } }, popupTemplate: '

Man Hole

Diameter	{mh_dia} ft.

Depth	{mh_depth} ft.

Address	{street_add}

Flows To	{wwtp} WWTP

', singlePopup: true });
Flood Zones
One huge benefit when using CartoDB is that we get direct SQL access to the PostGIS database. In this example we're using the ST_Simplify
function to trim down the number of vertices on returned geometry so that features appear a little quicker. This isn't necessary on all data sets but is helpful when dealing with complex geometries.
Keep in mind when performing geometric functions with SQL, your output geometry must be in a field named the_geom
to return proper GeoJSON.
cartodb_flood_zones = new lvector.CartoDB({ user: "geojason", table: "flood_zones", fields: "cartodb_id,label,st_simplify(the_geom,0.000008) the_geom", scaleRange: [14, 20], symbology: { type: "unique", property: "label", values: [ { value: "AE", vectorOptions: { fillColor: "#2f952f", fillOpacity: 0.6, weight: 1, color: "#fff", opacity: 0 } }, { value: "AE-FW", vectorOptions: { fillColor: "#004a00", fillOpacity: 0.6, weight: 1, color: "#fff", opacity: 0 } }, { value: "0.2% Annual Chance", vectorOptions: { fillColor: "#aaff7a", fillOpacity: 0.6, weight: 1, color: "#fff", opacity: 0 } } ], }, popupTemplate: '

Flood Zone

Type	{label}

', singlePopup: true });


Custom Specificity for CSS Rules
Syntax
respec(selector, specificity, rule)
selector
is a CSS selector
specificity
is a number 0 or greater
rule
is one or more CSS declarations separated by semicolons
Example
respec('div', 3, 'background: lime;')
Demo
tests/index.html
Github
https://github.com/tomhodgins/respec/


Packages
com.developmentarc.core.actions
com.developmentarc.core.actions.actions
com.developmentarc.core.actions.commands
com.developmentarc.core.controllers
com.developmentarc.core.controllers.interfaces
com.developmentarc.core.datastructures.utils
com.developmentarc.core.services
com.developmentarc.core.services.dispatchers
com.developmentarc.core.services.events
com.developmentarc.core.services.mocks
com.developmentarc.core.services.parsers
com.developmentarc.core.services.requests
com.developmentarc.core.tasks
com.developmentarc.core.tasks.events
com.developmentarc.core.tasks.groups
com.developmentarc.core.tasks.tasks
com.developmentarc.core.utils
com.developmentarc.core.utils.events


|
GAUSS Engine
0.4.0
Language bindings for the GAUSS Engine
|
GAUSS Array symbol type. More...
#include <gearray.h>
Public Member Functions | |
| GEArray () | |
| Initialize a one dimensional array with a single element set to zero. | |
| GEArray (std::vector< int > orders, VECTOR_DATA(double) data, bool complex=false) | |
| Initialize an array with the orders specified. More... | |
| GEArray (const int *orders, int orders_len, const double *data, int data_len, bool complex=false) | |
| GEMatrix * | getPlane (std::vector< int > orders, bool imag=false) const |
| Retrieve a 2-dimensional slice from an array. More... | |
| std::vector< double > | getVector (std::vector< int > orders, bool imag=false) const |
| Retrieve a one dimensional std::vector from an array. More... | |
| double | getElement (std::vector< int > orders, bool imag=false) const |
| Retrieve an element from an array. More... | |
| bool | setElement (double, std::vector< int > orders, bool imag=false) |
| Set an element in an array. More... | |
| std::vector< double > | getData (bool imag=false) const |
| Retrieve a copy of underlying numeric std::vector. More... | |
| std::vector< double > | getImagData () const |
| Retrieve underlying imaginary data storage. More... | |
| std::vector< int > | getOrders () const |
| Retrieve the std::vector of array orders. More... | |
| int | getDimensions () const |
| Return the number of array dimensions. More... | |
| virtual int | size () const |
| Returns the total element count. More... | |
| virtual std::string | toString () const |
| Returns a std::string representation of this object. | |
| virtual void | clear () |
| Clear all corresponding symbol data. More... | |
| Array_t * | toInternal () |
| Public Member Functions inherited from GESymbol | |
| virtual int | getRows () const |
| Return row count. More... | |
| virtual int | getCols () const |
| Return column count. More... | |
| virtual bool | isComplex () const |
| Return if data is complex. More... | |
| int | type () const |
Friends | |
| class | GAUSS |
| class | GAUSSPrivate |
Additional Inherited Members | |
| Protected Member Functions inherited from GESymbol | |
| GESymbol (int type) | |
| virtual void | setRows (int) |
| virtual void | setCols (int) |
| virtual void | setComplex (bool) |
| Protected Attributes inherited from GESymbol | |
| int | rows_ |
| int | cols_ |
| bool | complex_ |
| int | type_ |
GAUSS Array symbol type.
This represents An N-dimensional array of double precision numbers.
| GEArray::GEArray | ( | std::vector< int > | orders, |
| VECTOR_DATA(double) | data, | ||
| bool | complex = false |
||
| ) |
Initialize an array with the orders specified.
You need to fill in the array data from lowest dimension to highest dimension. If the data is complex, it should contain all the real values in the first half of the array, followed by all the imaginary values in the second half of the array.
Example:
Python
PHP
will create a complex array with the elements filled in as follows:
| orders | Dimension orders from highest to lowest left-to-right. |
| data | Data in one dimensional format |
| complex | True if array is complex, false otherwise. |
|
virtual |
| std::vector< double > GEArray::getData | ( | bool | imag = false | ) | const |
Retrieve a copy of underlying numeric std::vector.
Imaginary data can also be queried by supplying the imag argument, thus appending it to the end of the real data. Omitting or specifying the imag argument as false
will return only real data. If you wish to only view the imaginary data, there is a getImagData() method for convenience.
Example:
Python
PHP
will result in the output:
| imag | Whether to append imaginary data to end of real data |
| int GEArray::getDimensions | ( | ) | const |
Return the number of array dimensions.
This should be equal to the length of getOrders()
Example:
Python
PHP
will result in the output:
| double GEArray::getElement | ( | std::vector< int > | indices, |
| bool | imag = false |
||
| ) | const |
Retrieve an element from an array.
The indices array will contain N normal indices into the array, indicating the element you want. This function only returns either the real or the imaginary part of the data based on the imag argument
Example:
Python
PHP
will result in the output:
extracted from the values of a:
| indices | Indices indicating the element to retrieve |
| imag | Whether to return imaginary data instead of real data. |
| std::vector< double > GEArray::getImagData | ( | ) | const |
Retrieve underlying imaginary data storage.
This will be stored in lowest to highest dimension.
Example:
Python
PHP
will result in the output:
| std::vector< int > GEArray::getOrders | ( | ) | const |
Retrieve the std::vector of array orders.
These are ordered from highest to lowest.
Example:
Python
PHP
will result in the output:
| GEMatrix * GEArray::getPlane | ( | std::vector< int > | indices, |
| bool | imag = false |
||
| ) | const |
Retrieve a 2-dimensional slice from an array.
The indices array will contain N-2 normal indices into the array, positioning to the first element of the plane of interest, and two indices set to 0, indicating the dimensions of interest. The plane of elements across those 2 dimensions will be returned, the lower dimension becoming columns and the higher dimension becoming rows. This function returns either the real or the imaginary part of the data, based on the imag argument.
If you need to extract more than two dimensions of data, you can use the GAUSS indexing (square bracket) operators or the GAUSS.getArray(std::string) function. See the N-Dimensional Arrays and Working With Arrays chapters of the GAUSS User Guide.
Example:
Python
PHP
will result in the output:
extracted from the values of a:
| indices | Indices indicating the plane to retrieve, with 0's representing the dimensions of interest |
| imag | Whether to return imaginary data instead of real data. |
| std::vector< double > GEArray::getVector | ( | std::vector< int > | indices, |
| bool | imag = false |
||
| ) | const |
Retrieve a one dimensional std::vector from an array.
The dimension of interest must be specified with a 0. This will get a std::vector of elements across the dimension. This function only returns either the real or the imaginary part of the data based on the imag argument.
Example:
Python
PHP
will result in the output:
extracted from the value of a:
| indices | Indices that you would like to retrieve, with a 0 representing the dimension of interest |
| imag | Whether to return imaginary data instead of real data. |
| bool GEArray::setElement | ( | double | value, |
| std::vector< int > | indices, | ||
| bool | imag = false |
||
| ) |
Set an element in an array.
The indices array will contain N normal indices into the array, indicating the element you want to set the new value of. This function sets either the real or the imaginary part of the data based on the imag argument.
Example:
Python
PHP
will result in the output:
extracted from the values of a:
| value | Double precision value to set at element index |
| indices | Indices indicating the element to set |
| imag | Whether to set imaginary data instead of real data. |
|
virtual |
Returns the total element count.
This is the product of getOrders().
Reimplemented from GESymbol.


§484-18 Interstate rendition. In the proceedings for extradition of a person charged with a crime under this chapter, it need not be shown that the person whose surrender is demanded has fled from justice or at the time of the commission of the crime was in the demanding or other state. [L 1967, c 223, §18; HRS §484-18]


The Moniyan Empire of the Land of Dawn once enjoyed the blessings of angels. The Angel of Light, Rafaela, shone down on the people and healed all of their illnesses; the Angel of Dark, Argus, became the punisher of crime. Together they maintained peace and balance throughout the land.
Alucard was born in the capital of the empire. His parents were once mentors to Tigreal\'s Order of Knights. In one of his trials, Tigreal\'s overconfidence led to Alucard\'s parents sacrificing their lives in order to save him from demons. Unable to accept this harsh reality, Alucard went into the territory of the demons in order to search for his parents. All he found on the battlefield, however, was the family crest worn on his parents\' chest. He was then suddenly ambushed by the demons, who captured and tortured him for months. He was eventually freed by a demon hunter, after which he took up refuge as a resident of the Temple of Light.
Pada zaman prasejarah, seekor naga hitam muncul dari reruntuhan meteor yang jatuh di tanah Cadia Riverland. Dunia Oriental yang pada saat itu dikuasai oleh Great Dragon pun akhirnya berhasil diporak-poranda oleh sang naga hitam dan membawa kehancuran besar bagi tanah Cadia Riverland.
Johnson, with a hardy constitution as solid as a rock, ran through the dome stadium like a heavy truck, the cheers of girls bursting from everywhere. He led his team to lift the champion\'s trophy and achieved the highpoint of his life as a superstar quarterback with millions of fans. However, fortune is always fickle. A little girl suddenly rushed into the road while Johnson was driving his sports car. To avoid hitting the little girl he swerved and severely crashed his car. A massive hemorrhage was going to take his life quickly.
The birth of Saber traces back to the early years of Laboratory 1718. In the beginning, he was a scholar in one of the most famous invention teams in Scholar City. Dr. Rooney hoped that this team would be able to unlock the ultimate potential of mechanical invention and lead the world into a glorious age of technology. But the radically intellectual scientists became more and more obsessed with modifications to the human body. They engaged in insane experiments that ignored the limits of the human body. They were willing to try anything, use any combination of technology and power, so long as it enhanced human abilities that had not yet been unlocked by nature. Because of this, Dr. Rooney was forced to disband this team and banished the scientists.
There was a tale of a Great Dragon that had nine sons. They were unique to each other and responsible for their own duties. Seldom did the Great Dragon gather with his sons, however, as the adopted son, Zilong assisted the Great Dragon instead of the royal sons. In the eyes of the Great Dragon, Zilong was way better in his personalities and abilities, which made Zilong deeply trusted by him. Long ago, Zilong swore an oath to roam from world to world, assisting wise rulers by the Great Dragon\'s decree. Whenever a new king was in need of his strength, Zilong traverses space and time to remove all obstacles and enemies before the king, using spear fighting techniques endowed upon him by the Great Dragon. Now the Land of Dawn is in great danger and Zilong has come to its aid. With his sense of justice and bravery, Zilong defeated many enemies and his name spread among the land. Regardless of how strong the enemy was, Zilong\'s spear would not forgive any evil who tried to destroy this continent.
Long ago, the members of the House of Akakage were hailed as \"the Gods of Ninja Arts\". For generations, the Akakages researched and taught advanced ninjutsu. In order to reach the pinnacle of ninja arts, the Akakages used a forbidden ninjutsu to rid their hearts of evil, anger, and greed by condensing them into a demon called, Hanekage. No one expected that Hanekage would have consciousness, despite lurking within their bodies.
The Shura clan have thrived in isolation for countless generations, their men renowned for being the world\'s bravest fighters, and their women famed for being the world\'s greatest beauties. At the heart of the Shura clan\'s beliefs lies the legend of the Three Thousand Worlds. The legend speaks of three thousand secret worlds, which upon entering, one must face various levels of psychic trials and advance to world after world upon victory. The people of the Shura clan have discovered a way to enter these worlds, and only those who have conquered over three hundred worlds are granted the title of \"Ashura\", raising them to the level of a demigod in the eyes of their people. However, in the innumerable eons of Shura history, none managed to conquer the fabled three thousand worlds, until Martis appeared.
Franco\'s home is in the eternally frozen seas beyond the land of Northern Vale. This continent of ice and snow is where the sea people have made a life for themselves, but the resurrection of Captain Bane has destroyed their formerly peaceful lives. Franco and his comrades have banded together to oppose Bane\'s rule and bring peace back to the seas.


Name:
none
Requires:
Required by:
Produces:
Produced by:
Contains:
Contained by:
Graph layout
Force
Cluster
Show requires
0 (None)
1 (Direct only)
2
3
Show required-by
0 (None)
1 (Direct only)
2
3


jAY HOFFMANN
Front-end designer and developer, in love with the web.
Work
What I'm Doing
Writing
What I'm Thinking
Contact
Where To Find Me
Fill out my
online form
.
HTML Forms powered by
Wufoo


Bananas are good for your health.
Bananas are good.
A paragraph for the main content.
And another one.
Here's some contact info